1. Field of the Invention
The present invention relates to a method for predicting a traffic space mean speed and a traffic flow rate from a traffic density on a road, and further to a method and an apparatus for controlling a traffic light signaling system located at an intersection based upon the predicted traffic flow rate.
2. Description of the Related Art
Conventionally, to either maintain a smooth traffic condition, or construct a proper traffic system, traveling conditions of vehicles are measured to predict a traffic flow rate of the vehicles traveled on a road. Velocities of the vehicles traveling on the road are restricted by intervals among the successively traveling vehicles. As a consequence, an average velocity of a group of traveling vehicles may be predicted from a traffic density of the traveling vehicle group.
The conventional traffic flow rate predicting method is established under condition that the following relationship is satisfied.
That is, assuming now that a traffic flow rate is "q", a space mean speed is "v", and a traffic density is "k", a basic equation (1) can be satisfied: EQU q=kv (1)
It should be understood that a traffic space mean speed implies an arithmetic average value for velocities of vehicles located within a predetermined section on a road at a certain time instant, whereas a traffic density implies a quantity of vehicles present on a road in a unit length thereof at a certain time instant.
A relationship between the space mean speed "v" and the traffic density "k" is represented as a k-v curve in FIG. 4.
In FIG. 4, an abscissa indicates the traffic density "k" and an ordinate denotes the space mean speed "v". If the intervals among the successively traveling vehicles are narrow and the traffic density becomes high, then the vehicles could travel only in low speeds, resulting in a traffic jam. Eventually, the traffic density is brought into a jam density, so that a vehicle stream cannot be moved. Conversely, if the intervals among the successively traveling vehicles are wide and the traffic density becomes low, then a vehicle stream can be moved at high speeds. Eventually, each of these vehicles can freely travel at a velocity determined by the road conditions.
A crosspoint "kj" between the k-v curve and the abscissa represents a jam density, whereas a crosspoint "vf" between the k-v curve and the ordinate represents a free speed. Both of a curve pattern and these crosspoints may be determined based upon the road conditions and the like.
As a typical k-v relational expression fv(k), the following equation (2) is known. The equation (2) represents such a case that the traffic density "k" and the space mean speed "v" can satisfy a linear relationship. As explained above, when the space mean speed "v" is expressed by the traffic density "k", the traffic flow rate "q" becomes the function of only the traffic density "k", and therefore becomes a k-q curve as indicated in FIG. 5. This implies that the traffic flow rate may be predicted from the traffic density. EQU v=vf (1-k/kj) (2)
In a conventional control method for isolated traffic signals which are not intervened from other signals, a time gap control method for predicting traffic conditions based on time headways has been widely utilized that when the time headway is below than the threshold value, the green time is prolonged, and when the time headway exceeds the threshold value, a decision can be made that the saturation flow has passed through, whereby the green time is ceased.
A saturation flow implies such a traffic flow that vehicles travel while keeping a substantially minimum constant interval, and thus becomes a maximum flow rate of the vehicles at an incoming passage of a certain intersection. For instance, such a constant traffic flow corresponds to this saturation flow that if a vehicle stream is stopped at a traffic light, after turning-ON of the green light is commenced and approximately three vehicles located from the top position have passed, the subsequent vehicles are advanced.
FIG. 5 represents a relationship between a traffic flow rate and a traffic density in the conventional traffic flow rate predicting method. FIG. 5 indicates such a condition that a measurement is carried out for a unit time under constant traveling flow where no influence caused by the signaling control is given.
In FIG. 5, under a light traffic condition from traffic density of 0 to traffic density of "kc" at which the maximum traffic flow rate appears, when a total number of vehicles present within the section increases, the traffic flow rate also increases. However, when the traffic density exceeds "kc" and is brought into a heavy traffic condition, a smoothness of the vehicle traveling (average speed) is lowered and eventually, when the traffic density becomes "kj", no vehicle can travel. Accordingly, other than "kc", there are two traffic density conditions with respect to a certain traffic flow rate.
In the short time measurement of the road traffic flow where the influence caused by the traffic signal control is given, there is observed a large number of different vehicle distribution patterns even in the same traffic density. When too many vehicle groups are formed, the short time traffic flow rate approaches 0 irrespective of to the traffic density. As a consequence, the short-time traffic flow rate of the road traffic is present within an area surrounded by the curve and the abscissa shown in FIG. 5. This has been apparently proved by the actual traffic flow measurements obtained by the Applicant's experiments.
As described above, in accordance with the conventional traffic flow rate predicting method, there is such a problem that although the traffic flow rate obtained from the traffic density should be present on the "k-q" curve of FIG. 5, a plurality of actual short-time traffic flow rates would be present in an area surrounded by the X axis and the curve, which improperly reflects the actual traffic flow rate.
Also, in the conventional isolated traffic signal control method, there is another problem that since a certain time is required to directly measure the traffic flow rate, this measuring time may cause a delay control.
Further, in the above-explained conventional isolated traffic signal control method, since fluctuation in the time headway becomes large, depending on the different combinations of the preceding and succeeding vehicles, it is rather difficult to set the threshold values of the time headway. If a small threshold value is set, then a saturation flow would not pass through the cross-section thoroughly. Conversely, if a very large threshold value is set, then even when the saturation flow is ended, the green light signal would be continuously outputted vainly.
Then, in the above-explained conventional isolated traffic signal control method, the initial green time is previously set to a preselected constant green time, and the fixed initial green time is outputted even when no vehicle is located within the fixed initial green time. As a result, there is another problem that waste time happens to occur.
Moreover, in accordance with the conventional isolated traffic signal control method, since the input information used in the traffic signal control corresponds to a condition amount derived from the local data (quantity of passing vehicle and sensing pulse width), it is practically difficult to entirely grasp complex traffic flows.
JP-A-1-281598 issued to Soga et al describes that a recognition apparatus for recognizing the license plate of the vehicle traveling on the road is commonly utilized as the traffic-flow measurement apparatus by operating the switching unit. In this conventional recognition apparatus of Soga et al, when the traffic flow is measured, the viewing angle of the ITV camera used to pick up the image of the license plate is selected to be a large viewing angle so as to pick up image of the road. After the road image is inputted, the vehicle images are independently extracted one by one by way of the image processing techniques, thereby calculating the velocities, sorts, and quantity of passing vehicles. Although this conventional apparatus does not clearly disclose the concrete processing method for calculating the velocities and the like, since this apparatus utilizes such a processing technique for recognizing the numeral data indicated on the license plate, it seems that a very complex arithmetic calculation has been employed.
Marcy discloses a monitoring system in U.S. Pat. No. 4,390,951 which measures both of the mean overall speed of vehicles passing over the surveyed road section and the combined length of vehicles simultaneously present on the surveyed road, obtains an encumbrance parameter by diving the combined length by the mean overall speed to be recognized as a degree of loading of the road, and then controls the traffic lights corresponding to the traffic flow rate predicted from this encumbrance parameter. The monitoring system of Marcy must actually measure the velocities and the lengths of the respective vehicles passing the entrance and the exit of a predetermined road area, namely must measure a large number of elements, resulting in a complex monitoring system.
JP-A-3-273,400 by Naito discloses a method for measuring traveling conditions of traffic by employing a CCD camera by monitoring one typical vehicle selected from the traffic in order to predict the traffic conditions. This measuring system is to avoid such a difficulty in processing the image data for tracking a preselected vehicle without confusion for image recognition purposes, and is therefore to grasp the traveling conditions of a single vehicle in such a manner that a large quantity of measurement sampling areas are provided on the road monitored by the CCD camera, and the passages of the vehicles through these sampling areas are sequentially detected. Accordingly, this measuring system requires the mechanism to actually measure the velocities of the vehicles.